Computers are ubiquitous in society. For example, computers are present in everything from user-oriented desktop computer systems to complex networks of computers that facilitate credit card transactions. These complex networks represent a trend toward consolidating computers to implement high-density computing configurations, which are sometimes referred to as “data centers.” In fact, it is not uncommon for these data centers to include tens of thousands of servers or more. To support of these data centers, information technology (IT) professionals have had to shoulder new burdens that were previously not of concern to IT professionals: power consumption and temperature maintenance.
Previously, data center facilities managers were primarily responsible for providing the specified power to the computers within the data center and were also responsible for maintaining the ambient air conditions to match the specified operating conditions of the computers within the data center. Typically, power and cooling requirements of the data center were estimated based on the “name plate” ratings—an estimate of the power and cooling requirements provided by the computer manufacturer. Historically, when computer server power levels were low, this approach proved practical. More recently, however, IT professionals have begun implementing servers as “blade servers” where each chassis is filled with multiple server modules, or “blades.” Increasing the density of the servers in this manner may result in cooling costs for some data centers (e.g., 30,000 ft2) running into the tens of millions of dollars per year and also may result in a higher incidence of undesirable service outages caused by cooling failures.
Some facilities and IT professionals have begun to “de-rate,” or reduce the name plate power and cooling requirements by a fixed amount to increase the density of servers within a data center. De-rating, however, may still undesirably mis-predict actual power consumption. Other attempts to increase server density include estimating the actual power consumed with an anticipated application running on the server to provide a more accurate estimate of the actual power requirements of the server. However, an unexpected change in computing demand, for example as a result of a work load shift between servers, may increase power demand and trip a circuit breaker or cause localized over-heating.